{"628522":{"#nid":"628522","#data":{"type":"event","title":"ARC Colloquium: Xiaoming Huo (Georgia Tech)","body":[{"value":"\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EXiaoming Huo\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EMonday, November 11, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align = \u0022center\u0022\u003E\u003Cstrong\u003EKlaus 1116 East- 11:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003EHomotopic methods can significantly speed up the Computation of the Lasso-type of estimators\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u0026nbsp; \u003C\/strong\u003EIn optimization, it is well known that when the objective functions are strictly convex, gradient based approaches can be extremely effective, and most likely achieve the exponential rate in convergence. At the same time, the Lasso-type of estimator in general cannot achieve the optimal rate due to the undesirable behavior of the absolute function at the origin. The homotopic approach is to use a sequence of surrogate functions to approximate the L1 penalty in the Lasso-type of estimators. The approximating functions will converge to the L1 penalty in the Lasso estimator. At the same time, each approximating function is strictly convex and facilitates efficient numerical convergence. We demonstrate that by meticulously defined the surrogate functions, one can approve faster numerical convergence rate than any existing methods in computing for the Lasso-type of estimators. Our numerical simulations validate the above claim. We demonstrate the applications of the proposed methods in some cases.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/pwp.gatech.edu\/xiaoming-huo\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@Klauscc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Homotopic methods can significantly speed up the Computation of the Lasso-type of estimators - Klaus 1116 East at 11am"}],"uid":"27544","created_gmt":"2019-11-04 12:57:10","changed_gmt":"2019-11-04 12:57:10","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-11-11T11:00:00-05:00","event_time_end":"2019-11-11T12:00:00-05:00","event_time_end_last":"2019-11-11T12:00:00-05:00","gmt_time_start":"2019-11-11 16:00:00","gmt_time_end":"2019-11-11 17:00:00","gmt_time_end_last":"2019-11-11 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}